Using machine learning strategically
Using machine learning strategically
Artificial intelligence is much more than chatbots and smart assistants. This one-day workshop provides a sound and practical overview of machine learning (ML) and shows how specific business potential can be identified, evaluated and strategically categorised.
The course is aimed at employees with an interest in AI as well as managers who are responsible for or support data and ML projects. Based on the book A Practitioner's Guide to Machine Learning, the course provides a structured understanding of the opportunities, limitations and risks of ML applications.
More than hype: what machine learning can really do
Machine learning is not an end in itself. The workshop shows which problems can be usefully solved with ML - and where the limits of the technology lie. It also provides a clear understanding of how ML projects work, which building blocks are required and which prerequisites are crucial for sustainable success.
ML use cases are systematically developed and analysed using specific industry spotlights. This creates a solid understanding of business impact and strategic prioritisation.
Understanding risks. Avoid pitfalls.
Not every idea is suitable as a viable ML case. The training raises awareness of typical challenges - from data quality and availability to organisational framework conditions and unrealistic expectations.
Specific use cases are described and evaluated with the help of a structured ML project assessment. This provides a realistic picture of which projects deliver real added value and which risks need to be taken into account.
From the idea to the strategy
Finally, the strategic perspective is taken: What steps are required to anchor machine learning in the company in the long term?
Guidelines for a sound positioning are developed and concrete options for action for a successful long-term ML strategy are derived.
Dates:
- Dates on request
